Chapter 14 Sentiment Analysis using NRC Sentiment lexicon

We examine the following sentiments using NRC Sentiment lexicon

• Fear

• Surprise

• Joy

Mary Wollstonecraft Shelley is the most Fearful and most Surprising and most Joyful author.

Edgar Allen Poe is the least Fearful author.

HP Lovecraft is the least Surprising author.

HP Lovecraft is the least Joyful author.

14.1 Sentiment Analysis Words - Fear

The plot shows the authors with the Count of fear words.

plotEmotions = function(emotion,fillColor = fillColor2)
{
  nrcEmotions = get_sentiments("nrc") %>% 
  filter(sentiment == emotion)

train %>%
  unnest_tokens(word, text) %>%
  filter(!word %in% stop_words$word) %>%
  inner_join(nrcEmotions)  %>%
  group_by(author) %>%
  summarise(Count = n()) %>%
  ungroup() %>%
  mutate(author = reorder(author,Count)) %>%
  
  ggplot(aes(x = author,y = Count)) +
  geom_bar(stat='identity',colour="white", fill =fillColor) +
  geom_text(aes(x = author, y = 1, label = paste0("(",Count,")",sep="")),
            hjust=0, vjust=.5, size = 4, colour = 'black',
            fontface = 'bold') +
  labs(x = 'author', y = 'Count', 
       title = paste0('Author and ',emotion,' Words ')) +
  coord_flip() + 
  theme_bw()

}


plotEmotions("fear")

14.2 Fear Word Cloud - MWP

The following table and word cloud shows the fear words written by MWP , the most fearful author.

getEmotionalWords = function(emotion,author)
{
  nrcEmotions = get_sentiments("nrc") %>% 
    filter(sentiment == emotion) 
  
  emotionalWords = train %>%
    unnest_tokens(word, text) %>%
    filter(!word %in% stop_words$word) %>%
    filter(author == author) %>%
    inner_join(nrcEmotions) %>%
    group_by(word) %>%
    summarise(Count = n()) %>%
    arrange(desc(Count))
    
  
  return(emotionalWords)
  
}

FearWordsMWS = getEmotionalWords('fear','MWS')

kable(head(FearWordsMWS),"html") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>%
  scroll_box(width = "800px")

word	Count
death	380
fear	240
horror	198
doubt	159
terrible	146
change	136

wordcloud(FearWordsMWS$word, FearWordsMWS$Count, max.words = 30,colors=brewer.pal(8, "Dark2"))

14.3 Sentiment Analysis Words - Surprise

The plot shows the authors with the Count of Surprise words.

plotEmotions("surprise",fillColor)

14.4 Surprise Word Cloud - MWP

The following table and word cloud shows the surprising words written by MWP , the most surprising author.

SurpriseWordsMWS = getEmotionalWords('surprise','MWS')

kable(head(SurpriseWordsMWS),"html") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>%
  scroll_box(width = "800px")

word	Count
death	380
horror	198
hope	195
sun	167
wild	157
suddenly	151

wordcloud(SurpriseWordsMWS$word, SurpriseWordsMWS$Count, max.words = 30,colors=brewer.pal(8, "Dark2"))

14.5 Sentiment Analysis Words - Joy

The plot shows the authors with the Count of Joy words.

plotEmotions("joy",fillColor2)

14.6 Joy Word Cloud - MWP

The following table and word cloud shows the joy words written by MWP , the most joy author.

JoyWordsMWS = getEmotionalWords('joy','MWS')


kable(head(JoyWordsMWS),"html") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>%
  scroll_box(width = "800px")

word	Count
found	559
love	331
friend	270
hope	195
sun	167
beauty	154

wordcloud(JoyWordsMWS$word, JoyWordsMWS$Count, max.words = 30,colors=brewer.pal(8, "Dark2"))